AI Control Library / CF-07: Human Oversight & Escalation
Designation: Supplemental | Control types represented: Operational
Control requirement
Establish personnel acceptable-use policy for AI work, defining employee and contractor responsibilities for approved tools, information handling, output verification, action authority and reporting. Make the rules usable for assigned roles.
Why this matters
Technical controls cannot anticipate every judgment a person makes when using AI. Staff need clear responsibilities and a practical route for new uses or mistakes, beyond a general prohibition on unsafe behavior.
How the control types work together
Operational controls establish the assigned responsibilities, review processes and response decisions described here. Their effectiveness depends on performing the work and using evidence to guide action, rather than approving a document alone.
When it applies
Personnel interacting with organizational AI or using external AI for work, including developers, operators and business users.
Define the assessed boundary, dependencies and evidence limitations. Tailor depth and review frequency to potential impact, and document why a particular safeguard or exclusion is appropriate to the actual deployment.
Ownership
The AI policy owner coordinates HR, security and data-owner requirements; managers communicate and support compliance.
Implementation guidance
- Define role-relevant permitted and prohibited activities, including sensitive inputs, generated content, tool actions and personal accounts.
- Specify verification, approvals and reporting responsibilities with examples staff can recognize.
- Communicate policy and require appropriate acknowledgement, providing accessible advice and a new-use approval route.
- Review incidents and actual practices, updating policy and related training when gaps or confusing instructions appear.
How to verify it
Use representative records and authorized controlled tests. Identify the relevant version, operating conditions and expected result before testing, and retain enough evidence to support the conclusion.
| Test | Expected result |
|---|---|
| Present common role scenarios | Staff can identify the approved action or escalation. |
| Inspect access onboarding | Relevant policy responsibilities are communicated before use. |
| Review a changed AI feature | Personnel rules and training address new exposure. |
Record a finding when required results cannot be demonstrated or practice differs materially from the approved conditions. Missing evidence limits the conclusion; it should not be treated as a successful test.
Evidence to retain
- Personnel acceptable-use policy
- Communication and acknowledgement
- Scenario and adoption checks
- Policy revision records
Protect evidence according to its sensitivity, access needs and retention rules. Avoid unnecessary copies of personal information, secrets or confidential material, while preserving the records needed for authorized review.
If the control fails
Escalate repeated ambiguity or material misuse to the policy and role owners. Restrict affected use as needed and correct the process or training as well as individual behavior.
Example in practice
Hypothetical example: A salesperson wants an external assistant to rewrite a client proposal. The policy identifies approved tools, permitted data and review responsibilities before the proposed text is shared.
Related controls
- CF01-007: Acceptable Use Policy for AI Systems
- CF07-S11: AI Security Awareness Training
- CF07-S14: AI Acceptable Use – Personnel
Framework mappings
- CSA AICM (HRS-02)
- NIST AI RMF (GOVERN 1.1)
- ISO 42001 (Cl. 5.2)
Review and maintenance
Review at the interval approved by the control owner and after relevant changes, incidents or failed assessments. Update affected procedures and configuration, address evidence gaps and verify corrective action before closing findings.
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